The advantages of using this software include saving time, managing huge amounts of qualitative data, having increased flexibility, having improved validity and auditability of qualitative research, and being freed from manual and clerical tasks. Such software helps to organize, manage and analyse information. Previously there was very little capability to bring data in from other software packages. Although this was not the first standard to be proposed, it was the first to be implemented by more than one software package, and came as the result of a collaboration between vendors and community representatives from the research community. Initially support was included in Atlas.ti, QDA Miner, Quirkos and Transana, with implementation pledged from Dedoose, MAXQDA and NVivo. The aim is to allow users to bring coded qualitative data from one software package to another. In March 2019 the Rotterdam Exchange Format Initiative (REFI) launched a new open exchange standard for qualitative data called QDA-XML. Word extracting, statistical analysis, visualization Quantitative Discourse Analysis Package (qdap) ( R package) Text, audio, video, pictures, webpages, social networksĬoding, Aggregation, Query, Visualisation, Statistical ToolsĬoding, Statistical Tools, Visualisation, Query Windows, macOS, iOS, Android, Cloud (web-based)Ĭoding, Aggregation, Query, VisualisationĬoding, Query, Visualisation, Statistical Tools Text, Audio, Video, Graphic, Social Networks The CAQDAS networking project lists the following tools a CAQDAS program should have:Ĭomparison of CAQDAS software ApplicationĬoding, Sequence Analysis, Exploratory Data Analysis We () have written an article about Libro a while back listing all of it's features with screenshots.CAQDAS is used in psychology, marketing research, ethnography, public health and other social sciences. It can analyze text from different file format including text files, HTML files, ODF (OpenDocument format) and ePub (eBook format).
QUALITATIVE TEXT ANALYSIS SOFTWARE FREE FREE
Libro is text analysis and mining lightweight software, It was written in Python and Free Pascal/Lazarus. We have reviewed it briefly in this article.ĭataMelt has been used by many researchers for text-mining especially " Biomedical text mining". It also supports many scripting language. Even Though, it's a Java application the current version only supports Windows64.ĭataMelt is a free and open-source computation and visualization platform that supports many areas including text mining and analysis. It works on English, French and German documents.
It uses Open-NLP and comes with several NLP extensions. MbFXWords is a lightweight open-source text analysis and mining solution. It's very easy to use especially for beginners. It also supports unicode and non-uni-code text. Textable supports multiple input source, and formats (xml, csv, tsv, html). It has a large set of features and free recipe libraries. As it uses Orange it has its features like visual programming, visualization and scripting features. Textable is an amazing text mining and analysis tool which is uses Orange. It supports visual programming and comes packed with open-source algorithms and NLP libraries. TextFlow is a cloud-based for machine-learning, text mining and analysis. It has thematic models for technical models, support co-occurrence analysis, letter frequency analysis and central expressions. TexMiner supports multiple languages starting from English, French, Spanish, Russian and German. TexMiner is a free open-source generic text mining tool. Orange works seamlessly on Windows, Linux and macOS. It's has an interactive workflow, rich tool-set and comes with visual programming support. Orange is an open-source platform for machine learning, data analysis, text mining and data visualization. We will try to list the specific and unique features per item to make it easy for our readers to pick what they need.
So here in this article, we have collected several tools to help you achieve that, and even more, they are free and open-source as well. Ever wanted to analyze text documents for documents or articles? There are several tools, web services that provide such services but what about desktop programs?
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